Agent skill · software engineering · aiskillstore
apscheduler
Advanced Python Scheduler - Task scheduling and job queue system
Why this skill is useful
Provides specific scheduling patterns and examples for integrating APScheduler with Python applications that the AI wouldn't reliably generate on its own.
What it needs
Requires apscheduler installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
APScheduler APScheduler is a flexible task scheduling and job queue system for Python applications. It supports both synchronous and asynchronous execution with multiple scheduling mechanisms including cron-style, interval-based, and one-off scheduling. Quick Start Basic Synchronous Scheduler Async Scheduler with FastAPI Common Patterns Schedulers In-memory scheduler (development): Persistent scheduler (production): Distributed scheduler: Jobs Simple function jobs: Jobs with arguments: Async jobs: Triggers Interval trigger: Cron trigger: Date trigger (one-time): Calendar interval: Persistence SQLite: PostgreSQL: Redis (event broker): Job Management Get job results: Schedule management: Event handling: Configuration Task defaults: Job execution options: Requirements Dependencies by use case: Basic scheduling: apscheduler PostgreSQL persistence: asyncpg, sqlalchemy Redis distributed: redis MongoDB: motor SQLite: aiosqlite Best Practices 1. Use persistent storage for production to survive restarts 2. Set appropriate misfiregracetime to handle system delays 3. Use conflict policies when updating schedules 4. Subscribe to events for monitoring and debugging 5. Choose appropriate executors (threadpool for I/O, processpool for CPU) 6. Implement error handling in job functions 7. Use unique schedule IDs for management operations 8. Set result expiration to prevent memory leaks
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/apscheduler